2019
Overexpression of T-bet in HIV infection is associated with accumulation of B cells outside germinal centers and poor affinity maturation
Austin JW, Buckner CM, Kardava L, Wang W, Zhang X, Melson VA, Swanson RG, Martins AJ, Zhou JQ, Hoehn KB, Fisk JN, Dimopoulos Y, Chassiakos A, O'Dell S, Smelkinson MG, Seamon CA, Kwan RW, Sneller MC, Pittaluga S, Doria-Rose NA, McDermott A, Li Y, Chun TW, Kleinstein SH, Tsang JS, Petrovas C, Moir S. Overexpression of T-bet in HIV infection is associated with accumulation of B cells outside germinal centers and poor affinity maturation. Science Translational Medicine 2019, 11 PMID: 31776286, PMCID: PMC7479651, DOI: 10.1126/scitranslmed.aax0904.Peer-Reviewed Original ResearchMeSH KeywordsAdultAntibodies, NeutralizingAntibody AffinityAntigens, CD19B-LymphocytesCytokinesFemaleGerminal CenterHIV InfectionsHumansImmunologic MemoryLymph NodesMaleMiddle AgedMutation RatePhenotypeReceptors, Antigen, B-CellT-Box Domain ProteinsT-Lymphocytes, Helper-InducerTranscriptomeYoung AdultConceptsHIV-specific B cellsT-betGC B cellsGerminal centersB cellsLymph nodesPoor affinity maturationChronic immune activationMemory B cell compartmentAntibody-mediated immunityChronic infectious diseaseOptimal antibody responseB cell compartmentChronic human infectionsB cell receptorHIV viremiaImmunologic outcomesHIV infectionViremic individualsChronic viremiaImmune activationPeripheral bloodProtective antibodiesAntibody responseCD19
2015
The mutation patterns in B-cell immunoglobulin receptors reflect the influence of selection acting at multiple time-scales
Yaari G, Benichou JI, Vander Heiden J, Kleinstein SH, Louzoun Y. The mutation patterns in B-cell immunoglobulin receptors reflect the influence of selection acting at multiple time-scales. Philosophical Transactions Of The Royal Society B Biological Sciences 2015, 370: 20140242. PMID: 26194756, PMCID: PMC4528419, DOI: 10.1098/rstb.2014.0242.Peer-Reviewed Original ResearchMeSH KeywordsAntibody AffinityAntibody DiversityB-LymphocytesCell LineageClonal Selection, Antigen-MediatedComplementarity Determining RegionsGenes, ImmunoglobulinHumansImmunoglobulin Heavy ChainsImmunoglobulin Variable RegionModels, GeneticModels, ImmunologicalMutationReceptors, Antigen, B-CellSomatic Hypermutation, ImmunoglobulinTime FactorsConceptsLineage treesPositive selectionStrong selection pressureLong-term selectionInfluence of selectionGene familyVariable gene familiesComplementarity determining regionsClone membersMutation patternsSelection pressureB cell populationsImmunoglobulin genesB cellsFramework regionsSomatic hypermutationSomatic mutationsAffinity maturationMutationsClone sizeMaturation processLong trunkAffinity maturation processSignificant diversityMultiple rounds
2014
Influence of seasonal exposure to grass pollen on local and peripheral blood IgE repertoires in patients with allergic rhinitis
Wu YC, James LK, Vander Heiden J, Uduman M, Durham SR, Kleinstein SH, Kipling D, Gould HJ. Influence of seasonal exposure to grass pollen on local and peripheral blood IgE repertoires in patients with allergic rhinitis. Journal Of Allergy And Clinical Immunology 2014, 134: 604-612. PMID: 25171866, PMCID: PMC4151999, DOI: 10.1016/j.jaci.2014.07.010.Peer-Reviewed Original ResearchConceptsHealthy control subjectsNasal biopsy specimensAllergic rhinitisControl subjectsImmunoglobulin heavy chain geneBiopsy specimensIgE repertoireAllergic diseasesPeripheral bloodOngoing germinal center reactionsClonal relatednessNatural pollen exposureSeasonal allergic rhinitisPollen seasonRespiratory allergic diseasesIgH sequencesAntigen-driven selectionGerminal center reactionGrass pollen seasonBlood IgEAtopic statusIgG classAntibody classPatientsPollen exposureIntegrating B Cell Lineage Information into Statistical Tests for Detecting Selection in Ig Sequences
Uduman M, Shlomchik MJ, Vigneault F, Church GM, Kleinstein SH. Integrating B Cell Lineage Information into Statistical Tests for Detecting Selection in Ig Sequences. The Journal Of Immunology 2014, 192: 867-874. PMID: 24376267, PMCID: PMC4363135, DOI: 10.4049/jimmunol.1301551.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntibody AffinityAntibody DiversityB-Lymphocyte SubsetsCell LineageClonal Selection, Antigen-MediatedComputer SimulationConfounding Factors, EpidemiologicGene Rearrangement, B-LymphocyteGenes, ImmunoglobulinHumansMiceModels, ImmunologicalModels, StatisticalROC CurveSequence Analysis, DNASomatic Hypermutation, ImmunoglobulinVDJ ExonsConceptsLineage treesHigh-throughput sequencing technologyLineage tree shapesCell lineage informationIg sequencesRatio of replacementTree-shape analysisStatistical frameworkSequence-based methodsBinomial statistical analysisExperimental data setsIndicators of selectionSequencing technologiesLineage informationSequencing depthNumber of generationsData setsHybrid methodVivo selectionSilent mutationsTree shapeStatistical testsSequenceShape analysisMutations
2011
Detecting selection in immunoglobulin sequences
Uduman M, Yaari G, Hershberg U, Stern JA, Shlomchik MJ, Kleinstein SH. Detecting selection in immunoglobulin sequences. Nucleic Acids Research 2011, 39: w499-w504. PMID: 21665923, PMCID: PMC3125793, DOI: 10.1093/nar/gkr413.Peer-Reviewed Original Research
2009
Taking Advantage: High-Affinity B Cells in the Germinal Center Have Lower Death Rates, but Similar Rates of Division, Compared to Low-Affinity Cells
Anderson SM, Khalil A, Uduman M, Hershberg U, Louzoun Y, Haberman AM, Kleinstein SH, Shlomchik MJ. Taking Advantage: High-Affinity B Cells in the Germinal Center Have Lower Death Rates, but Similar Rates of Division, Compared to Low-Affinity Cells. The Journal Of Immunology 2009, 183: 7314-7325. PMID: 19917681, PMCID: PMC4106706, DOI: 10.4049/jimmunol.0902452.Peer-Reviewed Original ResearchConceptsLow-affinity B cellsLow-affinity cellsGerminal centersB cellsHigh-affinity B cellsHigh-affinity cellsDeath rateHigh death rateLower death ratesImmune responseHigh-affinity AbsB lymphocytesMemory responsesExtracellular pathogensSame AgPrimary responseGC reactionProliferative advantageSimilar ratesSurvivalCellsCell cycleControl of survivalHigh affinityResponse
2008
Getting Started in Computational Immunology
Kleinstein SH. Getting Started in Computational Immunology. PLOS Computational Biology 2008, 4: e1000128. PMID: 18769677, PMCID: PMC2518523, DOI: 10.1371/journal.pcbi.1000128.Peer-Reviewed Original Research
2003
Why are there so few key mutant clones? The influence of stochastic selection and blocking on affinity maturation in the germinal center
Kleinstein SH, Singh JP. Why are there so few key mutant clones? The influence of stochastic selection and blocking on affinity maturation in the germinal center. International Immunology 2003, 15: 871-884. PMID: 12807826, DOI: 10.1093/intimm/dxg085.sgm.Peer-Reviewed Original Research
2001
Toward Quantitative Simulation of Germinal Center Dynamics: Biological and Modeling Insights from Experimental Validation
KLEINSTEIN S, SINGH J. Toward Quantitative Simulation of Germinal Center Dynamics: Biological and Modeling Insights from Experimental Validation. Journal Of Theoretical Biology 2001, 211: 253-275. PMID: 11444956, DOI: 10.1006/jtbi.2001.2344.Peer-Reviewed Original ResearchConceptsCenter dynamicsParticular mathematical modelOrdinary differential equationsGerminal center dynamicsImmune system dynamicsDifferential equationsExperimental dataMathematical modelStochastic frameworkAverage dynamicsSpecific experimental dataDeterministic modelSystem dynamicsModel parametersPossible extensionsGeneral methodologyQuantitative simulationOpreaNew implementationDynamicsModeling insightsPerelsonCenter behaviorEquationsExperimental validation